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Wheat Grain Protein Content Estimation Based on Multi-temporal Remote Sensing Data and Generalized Regression Neural Network

文献类型： 外文期刊

作者： Li, Cunjun 1 ; Wang, Qian 1 ; Wang, Jihua 1 ; Wang, Yan 1 ; Yang, Xiaodong 1 ; Song, Xiaoyu 1 ; Huang, Wenjiang 1 ;

作者机构： 1.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

关键词： wheat;grain protein content;multi-temporal;Landsat;generalized regression neural network

期刊名称：COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE V, PT II

ISSN： 1868-4238

年卷期： 2012 年 369 卷

页码：

收录情况： SCI

摘要： Monitoring grain protein content in large areas by remote sensing is very important for guiding graded harvest, and facilitates grain purchasing for processing enterprises. Wheat grain protein content (GPC) at maturity was measured and multi- temporal Landsat TM and Landsat ETM + images at key stages in 2003, 2004 growth stages were acquired in this study. GPC was estimated with multi-temporal remote sensing data and generalized regression neural network (GRNN) method. Results show that the GPC prediction accuracy of the GRNN model is higher, with the average relative deviation of self-modeling, average relative deviation of cross-validation as 0.003%, 0.321%; 4.300%, 7.349% for 2003 and 2004 respectively. GRNN method proves to be reliable and robust to monitoring GPC in large areas by multi-temporal and multi-spectral remote sensing data.

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